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1 Sharp prediction of extinction times is needed in biodiversity monitoringand conservation management. 2 The Galton-Watson process is a classicalstochastic model for describing population dynamics. Its evolution is like thematrix population model where offspring numbers are random. Extinctionprobability, extinction time, abundance are well known and given by explicitformulas. In contrast with the deterministic model, it can be applied to smallpopulations. 3 Parameters of this model can be estimated through the Bayesianinference framework. This enables to consider non-arbitrary scenarios. 4 Weshow how coupling Bayesian inference with the Galton-Watson model providesseveral features: i) a flexible modelling approach with easily understandableparameters ii) compatibility with the classical matrix population model (Leslietype model) iii) A non-computational approach which then leads to moreinformation with less computing iv) a non-arbitrary choice for scenarios,parameters... It can be seen to go one step further than the classical matrixpopulation model for the viability problem. 5 To illustrate these features, weprovide analysis details for two examples whose one of which is a real lifeexample.

Galton-Watson process and bayesian inference: A turnkey method for the viability study of small populations